The ethical data scientist would strive to improve the world, not repeat it. That would mean deploying tools to explicitly construct fair processes. As long as our world is not perfect, and as long as data is being collected on that world, we will not be building models that are improvements on our past unless we specifically set out to do so.

At the very least it would require us to build an auditing system for algorithms. This would be not unlike the modern sociological experiment in which job applications sent to various workplaces differ only by the race of the applicant—are black job seekers unfairly turned away? That same kind of experiment can be done directly to algorithms; see the work of Latanya Sweeney, who ran experiments to look into possible racist Google ad results. It can even be done transparently and repeatedly, and in this way the algorithm itself can be tested.

The ethics around algorithms is a topic that lives only partly in a technical realm, of course. A data scientist doesn’t have to be an expert on the social impact of algorithms; instead, she should see herself as a facilitator of ethical conversations and a translator of the resulting ethical decisions into formal code. In other words, she wouldn’t make all the ethical choices herself, but rather raise the questions with a larger and hopefully receptive group.
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First, the link for the Modeler’s Hippocratic Oath takes you to a splash page at Wiley for Derman’s book: My Life as a Quant: Reflections on Physics and Finance.

I commend the entire text of The Financial Modelers’ Manifesto to you for repeated reading but for present purposes, let’s look at the Modelers’ Hippocratic Oath:

~ I will remember that I didn’t make the world, and it doesn’t satisfy my equations.

~ Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.

~ I will never sacrifice reality for elegance without explaining why I have done so.

~ Nor will I give the people who use my model false comfort about its accuracy. Instead, I will make explicit its assumptions and oversights.

~ I understand that my work may have enormous effects on society and the economy, many of them beyond my comprehension

It may just be me but I don’t see a charge being laid on data scientists to be the ethical voices in organizations using data science.

Do you see that charge?

To to put it more positively, aren’t other members of the organization, accountants, engineers, lawyers, managers, etc., all equally responsible for spurring “ethical conversations?” Why is this a peculiar responsibility for data scientists?

I take a legal ethics view of the employer – employee/consultant relationship. The client is the ultimate arbiter of the goal and means of a project, once advised of their options.

Their choice may or may not be mine but I haven’t ever been hired to play the role of Jiminy Cricket.

It’s heady stuff to be responsible for bringing ethical insights to the clueless but sometimes the clueless have ethical insights on their on, or not.

Data scientists can and should raise ethical concerns but no more or less than any other member of a project.

As you can tell from reading this blog, I have very strong opinions on a wide variety of subjects. That said, unless a client hires me to promote those opinions, the goals of the client, by any legal means, are my only concern.

PS: Before you ask, no, I would not work for Donald Trump. But that’s not an ethical decision. That’s simply being a good citizen of the world.

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